video model · wan · Windows

Can I run Wan 2.1 T2V 1.3B on AMD Ryzen AI Halo (128GB)?

Compatibility verdict VRAM check

Yes, it runs fast on this GPU

Yes. Wan 2.1 T2V 1.3B runs on AMD Ryzen AI Halo (128GB) at Q4 GGUF (~6 GB of ~96 GB usable).

Needs ~6 GB Device usable ~96 GB

Runs at Q4 GGUF using ~6 GB of ~96 GB usable.

Peak VRAM: ~6 GB
Usable on device: ~96 GB
Device memory: 128 GB
Quant: Q4 GGUF

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How to run it

Use ComfyUI or Diffusers at Q4 GGUF. The big text encoder is loaded to encode your prompt, then offloaded before generation, which is why peak VRAM stays near the backbone size rather than the sum of every file.

Model wan

Type: video (DIT)
Parameters: 1.3B
Peak VRAM: ~6 GB at Q4 GGUF
Resolution: 832×480 (480p)
License: Apache-2.0

Full Wan 2.1 T2V 1.3B requirements →

Device Windows

Memory: 128 GB unified
Usable for weights: ~96 GB
Power draw: ~120 W
Best runtime: llama.cpp (Vulkan/ROCm) / LM Studio

Best models for AMD Ryzen AI Halo (128GB) →

You could also run

Run Wan 2.1 T2V 1.3B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Apple M2 (16GB)Apple M4 (16GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)

FAQ

Can AMD Ryzen AI Halo (128GB) run Wan 2.1 T2V 1.3B?

Yes. Wan 2.1 T2V 1.3B runs on AMD Ryzen AI Halo (128GB) at Q4 GGUF (~6 GB of ~96 GB usable).

How much VRAM does Wan 2.1 T2V 1.3B need?

AMD Ryzen AI Halo (128GB) has room to spare. At Q4 GGUF the realistic peak is ~6 GB of VRAM, versus ~20 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~5 GB, much slower.

What do I use to run Wan 2.1 T2V 1.3B locally?

Wan 2.1 T2V 1.3B runs in ComfyUI or Diffusers. It loads as a video diffusion checkpoint plus its text encoder and VAE, not a single chat command.

Sources

VRAM figures are sourced peak-usage anchors at the noted quant, validated 2026-08-03. See methodology.